Esempio n. 1
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    def compute_fov(
        self,
        x: int,
        y: int,
        radius: int = 0,
        light_walls: bool = True,
        algorithm: int = tcod.constants.FOV_RESTRICTIVE,
    ) -> None:
        """Compute a field-of-view on the current instance.

        Args:
            x (int): Point of view, x-coordinate.
            y (int): Point of view, y-coordinate.
            radius (int): Maximum view distance from the point of view.

                A value of `0` will give an infinite distance.
            light_walls (bool): Light up walls, or only the floor.
            algorithm (int): Defaults to tcod.FOV_RESTRICTIVE

        If you already have transparency in a NumPy array then you could use
        :any:`tcod.map_compute_fov` instead.
        """
        if not (0 <= x < self.width and 0 <= y < self.height):
            warnings.warn(
                "Index (%r, %r) is outside of this maps shape (%r, %r)."
                "\nThis will raise an error in future versions."
                % (x, y, self.width, self.height),
                RuntimeWarning,
                stacklevel=2,
            )

        lib.TCOD_map_compute_fov(
            self.map_c, x, y, radius, light_walls, algorithm
        )
Esempio n. 2
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    def compute_fov(
        self,
        x: int,
        y: int,
        radius: int = 0,
        light_walls: bool = True,
        algorithm: int = tcod.constants.FOV_RESTRICTIVE,
    ) -> None:
        """Compute a field-of-view on the current instance.

        Args:
            x (int): Point of view, x-coordinate.
            y (int): Point of view, y-coordinate.
            radius (int): Maximum view distance from the point of view.

                A value of `0` will give an infinite distance.
            light_walls (bool): Light up walls, or only the floor.
            algorithm (int): Defaults to tcod.FOV_RESTRICTIVE

        If you already have transparency in a NumPy array then you could use
        :any:`tcod.map_compute_fov` instead.
        """
        lib.TCOD_map_compute_fov(
            self.map_c, x, y, radius, light_walls, algorithm
        )
Esempio n. 3
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    def compute_fov(self,
                    x,
                    y,
                    radius=0,
                    light_walls=True,
                    algorithm=lib.FOV_RESTRICTIVE):
        """Compute a field-of-view on the current instance.

        Args:
            x (int): Point of view, x-coordinate.
            y (int): Point of view, y-coordinate.
            radius (int): Maximum view distance from the point of view.

                A value of `0` will give an infinite distance.
            light_walls (bool): Light up walls, or only the floor.
            algorithm (int): Defaults to tcod.FOV_RESTRICTIVE
        """
        lib.TCOD_map_compute_fov(self.map_c, x, y, radius, light_walls,
                                 algorithm)
Esempio n. 4
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def compute_fov(
    transparency: np.ndarray,
    pov: Tuple[int, int],
    radius: int = 0,
    light_walls: bool = True,
    algorithm: int = tcod.constants.FOV_RESTRICTIVE,
) -> np.ndarray:
    """Return a boolean mask of the area covered by a field-of-view.

    `transparency` is a 2 dimensional array where all non-zero values are
    considered transparent.  The returned array will match the shape of this
    array.

    `pov` is the point-of-view origin point.  Areas are visible if they can
    be seen from this position.  `pov` should be a 2D index matching the axes
    of the `transparency` array, and must be within the bounds of the
    `transparency` array.

    `radius` is the maximum view distance from `pov`.  If this is zero then
    the maximum distance is used.

    If `light_walls` is True then visible obstacles will be returned, otherwise
    only transparent areas will be.

    `algorithm` is the field-of-view algorithm to run.  The default value is
    `tcod.FOV_RESTRICTIVE`.
    The options are:

    * `tcod.FOV_BASIC`:
      Simple ray-cast implementation.
    * `tcod.FOV_DIAMOND`
    * `tcod.FOV_SHADOW`:
      Recursive shadow caster.
    * `tcod.FOV_PERMISSIVE(n)`:
      `n` starts at 0 (most restrictive) and goes up to 8 (most permissive.)
    * `tcod.FOV_RESTRICTIVE`

    .. versionadded:: 9.3

    .. versionchanged:: 11.0
        The parameters `x` and `y` have been changed to `pov`.

    Example:
        >>> explored = np.zeros((3, 5), dtype=bool, order="F")
        >>> transparency = np.ones((3, 5), dtype=bool, order="F")
        >>> transparency[:2, 2] = False
        >>> transparency  # Transparent area.
        array([[ True,  True, False,  True,  True],
               [ True,  True, False,  True,  True],
               [ True,  True,  True,  True,  True]]...)
        >>> visible = tcod.map.compute_fov(transparency, (0, 0))
        >>> visible  # Visible area.
        array([[ True,  True,  True, False, False],
               [ True,  True,  True, False, False],
               [ True,  True,  True,  True, False]]...)
        >>> explored |= visible  # Keep track of an explored area.

    .. seealso::
        :any:`numpy.nonzero`
        :any:`numpy.choose`
        :any:`numpy.select`
    """
    transparency = np.asarray(transparency)
    if len(transparency.shape) != 2:
        raise TypeError(
            "transparency must be an array of 2 dimensions"
            " (shape is %r)" % transparency.shape
        )
    if isinstance(pov, int):
        raise TypeError(
            "The tcod.map.compute_fov function has changed.  The `x` and `y`"
            " parameters should now be given as a single tuple."
        )
    if not (
        0 <= pov[0] < transparency.shape[0]
        and 0 <= pov[1] < transparency.shape[1]
    ):
        warnings.warn(
            "Given pov index %r is outside the array of shape %r."
            "\nThis will raise an error in future versions."
            % (pov, transparency.shape),
            RuntimeWarning,
            stacklevel=2,
        )
    map_ = Map(transparency.shape[1], transparency.shape[0])
    map_.transparent[...] = transparency
    lib.TCOD_map_compute_fov(
        map_.map_c, pov[1], pov[0], radius, light_walls, algorithm
    )
    return map_.fov